Articles | Volume 15, issue 8
https://doi.org/10.5194/amt-15-2547-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-2547-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An instrument for direct measurement of emissions: cooling tower example
Christopher D. Wallis
CORRESPONDING AUTHOR
Air Quality Research Center, University of California, Davis, CA
95616, USA
Mason D. Leandro
Department of Earth and Planetary Sciences, University of California, Santa Cruz, CA 95064, USA
Patrick Y. Chuang
Department of Earth and Planetary Sciences, University of California, Santa Cruz, CA 95064, USA
Anthony S. Wexler
Air Quality Research Center, University of California, Davis, CA
95616, USA
Department of Mechanical and Aerospace Engineering, University of California, Davis, CA 95616, USA
Department of Civil and Environmental Engineering, University of California, Davis, CA 95616, USA
Department of Land, Air, and Water Resources, University of California, Davis, CA 95616, USA
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Mikael Witte, Roya Bahreini, Sierra Bollinger, Anthony Bucholtz, Patrick Chuang, Don Collins, Minghao Han, Mason Leandro, Alexander MacDonald, Andrew Metcalf, Bradley Ries, Nimya Sunil, Dongli Wang, and Lisa Welp
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-593, https://doi.org/10.5194/essd-2026-593, 2026
Preprint under review for ESSD
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The Southern California Investigation of Low cloud and Land Aerosol (SCILLA) was an airborne experiment in June 2023. The goal was to understand how wind patterns and islands in the Southern California Bight affect airborne particulate matter and cloud drops. We flew a total of 20 flights. The aircraft had instruments to sample clouds, particulate matter, meteorology, and atmospheric gases. The paper describes how we flew, lists the instruments flown, and gives a summary of each flight.
Scarlet R. Passer, Mikael K. Witte, and Patrick Y. Chuang
Atmos. Meas. Tech., 18, 3819–3831, https://doi.org/10.5194/amt-18-3819-2025, https://doi.org/10.5194/amt-18-3819-2025, 2025
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One important property of a cloud is the concentration of cloud drops. This property is relevant to how the cloud interacts with sunlight and how easily the cloud forms precipitation. Measuring this property from satellite observations is one important source of data, but it does require making some assumptions. This study evaluates the accuracy of satellite-derived drop concentration by a comparison with aircraft measurements.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, P. Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankararaman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Johann Engelbrecht, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbigniew Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gómez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal L. Weagle, and Xi Zhao
Atmos. Chem. Phys., 25, 4665–4702, https://doi.org/10.5194/acp-25-4665-2025, https://doi.org/10.5194/acp-25-4665-2025, 2025
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Aerosol particles are an important part of the Earth system, but their concentrations are spatially and temporally heterogeneous, as well as being variable in size and composition. Here, we present a new compilation of PM2.5 and PM10 aerosol observations, focusing on the spatial variability across different observational stations, including composition, and demonstrate a method for comparing the data sets to model output.
Nagendra Raparthi, Anthony S. Wexler, and Ann M. Dillner
Atmos. Meas. Tech., 18, 603–618, https://doi.org/10.5194/amt-18-603-2025, https://doi.org/10.5194/amt-18-603-2025, 2025
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Quantifying the composition-dependent hygroscopicity of aerosol particles is essential for advancing our understanding of atmospheric processes. Existing methods do not integrate chemical composition with hygroscopicity. We developed a novel method to assess the water uptake of particles sampled on aerosol filters at relative humidity levels up to 97 % and link it with their composition. This approach allows for the separation of total water uptake into inorganic and organic components.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankarararman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Hannele Hakola, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbiginiw Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gomez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal Weagle, and Xi Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-1, https://doi.org/10.5194/essd-2024-1, 2024
Preprint withdrawn
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Aerosol particles can interact with incoming solar radiation and outgoing long wave radiation, change cloud properties, affect photochemistry, impact surface air quality, and when deposited impact surface albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. Here we present a new compilation of aerosol observations including composition, a methodology for comparing the datasets to model output, and show the implications of these results using one model.
Mampi Sarkar, Adriana Bailey, Peter Blossey, Simon P. de Szoeke, David Noone, Estefanía Quiñones Meléndez, Mason D. Leandro, and Patrick Y. Chuang
Atmos. Chem. Phys., 23, 12671–12690, https://doi.org/10.5194/acp-23-12671-2023, https://doi.org/10.5194/acp-23-12671-2023, 2023
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We study rain evaporation characteristics below shallow cumulus clouds over the North Atlantic Ocean by pairing isotope observations with a microphysical model. The modeled fraction of rain mass that evaporates below the cloud strongly depends on the raindrop size and distribution width. Moreover, the higher the rain mass fraction evaporated, the greater the change in deuterium excess. In this way, rain evaporation could be studied independently using only isotope and microphysical observations.
Bruno Debus, Andrew T. Weakley, Satoshi Takahama, Kathryn M. George, Anahita Amiri-Farahani, Bret Schichtel, Scott Copeland, Anthony S. Wexler, and Ann M. Dillner
Atmos. Meas. Tech., 15, 2685–2702, https://doi.org/10.5194/amt-15-2685-2022, https://doi.org/10.5194/amt-15-2685-2022, 2022
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In the US, routine particulate matter composition is measured on samples collected on three types of filter media and analyzed using several techniques. We propose an alternate approach that uses one analytical technique, Fourier transform-infrared spectroscopy (FT-IR), and one filter type to measure the chemical composition of particulate matter in a major US monitoring network. This method could be used to add low-cost sites to the network, fill-in missing data, or for quality control.
Patrick Obin Sturm and Anthony S. Wexler
Geosci. Model Dev., 15, 3417–3431, https://doi.org/10.5194/gmd-15-3417-2022, https://doi.org/10.5194/gmd-15-3417-2022, 2022
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Large air quality and climate models require vast amounts of computational power. Machine learning tools like neural networks can be used to make these models more efficient, with the downside that their results might not make physical sense or be easy to interpret. This work develops a physically interpretable neural network that obeys scientific laws like conservation of mass and models atmospheric composition more accurately than a traditional neural network.
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Short summary
Measuring emissions from stacks requires techniques to address a broad range of conditions and measurement challenges. Here we describe an instrument package held by a crane above a stack to characterize both wet droplet and dried aerosol emissions from cooling tower spray drift in situ. The instrument package characterizes the velocity, size distribution, and concentration of the wet droplet emissions and the mass concentration and elemental composition of the dried PM2.5 and PM10 emissions.
Measuring emissions from stacks requires techniques to address a broad range of conditions and...